Landscape Characterization and Dynamics of Oases in Arid Environments

Stability of patches of oasis landscape in arid areas: A case study of Sangong River Watershed, Xinjiang, China

Lost forever? Ecosystem functional changes occurring after agricultural abandonment and forest recovery in the semiarid Chaco forests

Geographic information systems (GIS), their fundamental components and technologies are described. GIS is a computer-based system enabling the storage, integration, query, display and analysis of data using information on data location. Further, remote sensing (RS) methods and their application in landscape characterization are described. Landscape pattern analysis, combined with statistical analysis, allows the determination of landscape predictors of disease risk. This makes RS/GIS a powerful set of tools for disease surveillance, enabling the prediction of potential disease outbreaks and targeting intervention programs. The 'pre-GIS era' is briefly described including the early mapping of tick distribution, analyses and the display of biogeographical and medical data. The theory of natural focality of diseases (NFD) is explained and its significance in tick-borne diseases (TBD) research is discussed. Many problems of tick ecology and TBD epidemiology and epizootology have been addressed by means of GIS and examples of these studies are presented and discussed.

Hardly any part of the world has remained unchanged since the arrival of the speciesHomo sapiens including the mountain ecosystems. Himalayan physiographic unit of India in due course has become populated and is tolerating all kinds of human interventions. Soil erosion in this region has been identified as a major problem due to both natural and anthropogenic factors. Remote sensing and Geographical Information system (GIS) techniques hold great promises in the assessment and conservation of natural resources including the surface soil. The major objective of the present study was to apply a process based model to quantify soil erosion and to prioritize the sub-watershed on this basis. The sub-watershed located at Jakhan rao area of Western Dun in lower Himalayan belt was taken as the test site for the study at 1: 50,000 scale. Deforestation, unscientific agricultural practices, terrace farming, cattle grazing and land degradation in the sub-watershed are some of the anthropogenic factors causing soil erosion in the area. Here, MMF model was used for estimation of soil erosion by incorporating layers derived from both remote sensing and ancillary data. IRS 1C LISS III satellite data was used for the preparation of land use map that was used to derive RD map, BD map and K map. Digital Elevation Model (DEM) provided slope map, an intermediate layer used in equation 6 to generate G map, and soil map provided MS map, BD map and K map. The above intermediate layers generated were then integrated in GIS domain to estimate the amount of soil erosion in the sub-watershed area. Results show high values 4572.333 kg/m2 for G map, which depicted transport capacity of overland flow. Comparatively lower values 13.15, and 7.98 kg/m2were observed for F map, which depicted soil detachment by raindrop impact. The subtracted image of the aforesaid layers produced the real picture, where in the highest value 3.770 kg/m2 was found in the midland region of the site. The crossed erosion map was then classified into different erosion classes for sub-watershed area. This study illustrates the applications of remote sensing and GIS techniques for soil erosion modeling.

Joint learning with GIS: multi-actor resource management

Initial delineation of prospecting zones of groundwater was conducted in the present study using remote sensing and geographic information system (GIS) techniques. It has been preparing an integrated geographic database of spatial and non-spatial data for the study area. The spatial data were generated by using image processing software (Erdas 8.3) and GIS software (Arc view 3.3) enhanced by real frequent field visits of the study area. These data include: surface features which give a direct and indirect indicators of the existence of groundwater and affect to the groundwater movement such as hydrogeomorphological, drainage density, slope, landuse and soil maps. The non spatial data were derived primarily from real views during field visits to the study area and from the existing writing or previous studies. All the data generated were saved in the GIS databank for the purpose of digitization, computational and generate the best possible output results to determine the extent of possible areas where the water that exists for the purpose of prospecting. Results showed that more areas could be have very good categories of prospect zones are the southern parts of the study area, which covers about 375 Km2 while the northern areas, which covers about 164 Km2 of the study area are grouped as runoff zone. Accordingly the possibilities of the presence of groundwater are poor to negligible in this zone. The current study demonstrated that a remote sensing and GIS technique are very effective tools that can give the initial predictions on the presence or probability of the presence of ground water in areas which have the same considered geological deposits for the study area.

Terrace agriculture in a mountainous arid environment – A study of soil quality and regolith provenance: Jabal Akhdar (Oman)

In Vietnam, the remarkable economic growth that resulted from the doi moi (renovation) reforms was based largely on the rural households that had become the new basic unit of agricultural production in the early 1990s. The technical, economic, and social changes that accompanied the decollectivization process transformed agricultural production, resource management, land use, and the institutions that defined access to resources and their distribution. Combined with the extreme biophysical, technical, and social heterogeneity encountered in the northern mountains, these rapid changes led to the extreme complexity of the agrarian dynamics that today challenges traditional diagnostic approaches. Since 1999, a participatory simulation method has been developed to disentangle the cause-and-effect relationships between the different driving forces and changes in land use observed at different scales. Several tools were combined to understand the interactions between human and natural systems, including a narrative conceptual model, an agent-based spatial computational model (ABM), a role-playing game, and a multiscale geographic information system (GIS). We synthesized into an ABM named SAMBA-GIS the knowledge generated from the above tools applied to a representative sample of research sites. The model takes explicitly into account the dynamic interactions among: (1) farmers' strategies, i.e., the individual decision-making process as a function of the farm's resource profile; (2) the institutions that define resource access and usage; and (3) changes in the biophysical and socioeconomic environment. The next step consisted of coupling the ABM with the GIS to extrapolate the application of local management rules to a whole landscape. Simulations are initialized using the layers of the GIS, e.g., land use in 1990, accessibility, soil characteristics, etc., and statistics available at the village level, e.g., population, ethnicity, livestock, etc. At each annual time step, the agrarian landscape changes according to the decisions made by agent-farmers about how to allocate resources such as labor force, capital, and land to different productive activities, e.g., crops, livestock, gathering of forest products, off-farm activities. The participatory simulations based on SAMBA-GIS helped identify villages with similar land-use change trajectories to which the same types of technical and/or institutional innovations could be applied. Scenarios of land-use changes were developed with local stakeholders to assess the potential impact of these changes on the natural resource base and on agricultural development. This adaptive approach was gradually refined through interactions between researchers and the local population.

Oases of South Tunisia, plays an important role in environmental, social and economic aspects of this region. This research was conducted in ten regions located on the south which are affected by changes in conditions and composition of land cover change. For each study area, Landsat imagery, thematic maps and training data were acquired. These images were georeferenced and radiometrically corrected and landscapes product were generated using Decision Tree Classification. The landscapes typology were then evaluated using the extract oases. This study aimed to assess the potential of NDVI (Normalized Difference Vegetation Index) to determine oasis cover using medium spatial resolution remote sensing imagery in the south of Tunisia. It explores the possibility of identifying and mapping oasis landscape types by using remote sensing, Geographic Information Systems and statistical analysis. The superposition of environment types map obtained with oasis extracted from NDVI map has shown six oasis landscapes in southern Tunisia : Gafsa-ElGuettar, El Hamma de Gabes, Douz-Kebili, Rjim Maatoug, Tozeur-Nafta and Tamerza Chebika oases. This research paper allowed to define a methodology for the construction of landscape types, in a computerized way, based on remote sensing and GIS and its result can be a draft work to make an Atlas of the landscapes of our site of study or, it can be used as a basic document to monitor the spatial extension of agricultural perimeters in order to ensure the sustainable development of these particular agro-systems.

Effects of landscape structure on vegetation and some animal groups after agriculture abandonment

The soil erosion risk on the slopes in Luong Son District, Hoa Binh Province, Vietnam, was determined to inform sustainable land management and conservation planning. Remote sensing and geographic information system (GIS) technologies were integrated with the universal soil loss equation (USLE) model to generate thematic maps of rainfall erosivity (R), soil erodibility (K), topographic factors (LS), and vegetation cover. These maps were combined to produce a comprehensive soil erosion risk map. The results showed that 65.09% of the district (23,747.61 hectares), mainly flat and midland areas, had no erosion risk. Light, moderate, and severe erosion affected 19.95%, 7.61%, and 7.35% of the region, respectively. Higher erosion risk is concentrated in mid-level mountainous and limestone regions, characterized by steep slopes and sparse vegetation. These findings highlight the influence of slope gradient and length on erosion severity and spatial patterns. Remote sensing, GIS, and USLE were integrated to spatially assess soil erosion, providing a scientific basis for targeted interventions, such as reforestation and terrace farming. This study contributes to gaps in the literature by comprehensively analyzing spatial soil erosion risk and providing practical recommendations for mitigating soil erosion in vulnerable landscapes and supporting sustainable land use planning under climate change pressures.

Oasis agroecosystems monitoring plays a significant role in the economic development, sustainable management, and policy-making of arid and Saharan regions. The aims of this study are to analyze the spatiotemporal changes of oasis vegetation and discuss possible driving forces of changes. This analysis employed field and ancillary data, geographic information system, Landsat imagery, and remote-sensing techniques. Minimum noise fraction is used for endmembers extraction, and spectral mixture analysis is applied to each image to extract vegetation fraction, which is used as an indicator of change. Change detection is performed in six oases in south-eastern Morocco over eight separate periods from 1984 to 2017 using Landsat data. The pattern of the spatiotemporal changes in vegetation cover is analyzed using time- and space-oriented change detection algorithms. Results indicate that the Mezguita, Tinzouline, and Ternata oases had an evenly distributed and constant expansion during the last three decades (of ∼41.35 % ), whereas the oases of Fezouata and Ktaoua presented low expansion and randomly distributed change (∼29 % ). However, the vegetation cover of M’Hamid oasis decreased by 23% over the studied period. The results show that spectral mixture analysis yields high accuracies for oasis vegetation extraction in arid areas and accounts for mixed pixel issues. The results are discussed considering also climate and socioeconomic factors, showing that the driving forces of these dynamics are primarily anthropogenic.

This paper examines the problem of agricultural land abandonment through knowledge of driving factors. First, we reach out a review of the concept of abandonment in order to define the negative and positive aspects of this process in the landscape. Then we focus on a real case study in the Marina Baja region (SE Spain). Finally, we propose, from a theoretical perspective, the use of a methodology to define the most important variables for studying the abandonment processes in this region. First of all, we performed various analyses using Geographical Information Systems (GIS) to create a geodatabase which stores the main factors generally associated with abandonment. The variables considered can be grouped into three groups: environmental (such as climate, soils or relief), socio-economic (such as demographic, accessibility or technology) and those related to cultural practices in the crop (such as irrigation or rain-fed stone walls). Considering over a hundred variables we need to answer two questions: (1) which of the variables are really driving factors in the abandonment process of an agricultural plot? and (2) how important is each of them alone or in combination with others? The authors advocate the use of GIS for the feature creation or management and Data Mining techniques to perform the feature selection. Specifically, we propose the use of a concrete metric, aci (Attribute Correlation Index), to answer the questions raised above.

The recognition of landscape as cultural heritage has increasingly brought together work on landscape and heritage in recent years. In a practical sense, this has been recognised through effective landscape management strategies that have sought to encompass wider information on the historic environment and its associated values. Across Europe in recent years, effective assessment and management of the historic environment have developed through a conversation around such schemes as landscape character assessment (LCA) and historic landscape characterisation (HLC). Further work is required, however, in order to extend this conversation further in trans‐cultural contexts. This paper explores the possibilities of developing such a conversation through geographic information system (GIS) modelling that draws on both western LCA/HLC perspectives and Chinese Shan‐Shui philosophies. We believe that a creative conversation between western and Chinese landscape heritage philosophies might be able to allow landscape characterisation approaches that use GIS methodologies to attain a greater depth of heritage understanding within their operation. Through trans‐cultural exchange, therefore, this research explores how a novel and indigenous language (of Shan‐Shui characterisation) might enliven western LCA, thus providing a productive conversation between different disciplines, philosophies, and culture cognitions.

The current paper presents a study on the interaction between land abandonment and soil responses to fire in old agricultural terraced landscapes. The study area, located near the Guadalest reservoir (E Spain), was partially affected by a forest fire in August 1998. We monitored burned and unburned areas as well as two pre-fire stand ages since agricultural abandonment: 8–15 years (dry grassland with young Pinus halepensis) and >35 years (mature pine forest). We analysed soil surface structure, water repellency and infiltrability, and we monitored plant response, runoff and sediment production for a period of 7 years after the fire. Aggregate stability increased with both time-since-abandonment and fire. Water repellency increased with land abandonment but was not affected by fire. Unburned erosion plots produced almost no runoff, even during heavy rainstorms. Fire scarcely modified runoff and erosion rates in recently abandoned terraces. A dry period following fire restricted plant recovery in burned pine forest. Burned forest plots registered runoff and sediment yields one to four orders of magnitude higher than unburned forest plots. In burned pine forest, the maximum sediment production was registered 3 years after the fire, when rainstorms took place and plant cover was still low. Old agricultural terraces colonised by pines were found to be both vulnerable to degradation as a consequence of fire and highly dependent on post-fire rain for their recovery.